磁共振成像系统图像信噪比的检测方法

医用磁共振成像(MRI)系统是大型医用影像诊断设备,本文根据医用磁共振成像(MRI)系统的技术特性,参考国际标准,验证、推荐了一种图像信噪比检测方法,该方法科学、简便,可作为计量检测、医院质量控制的技术依据。     

磁共振成像设备图像均匀性及层厚检测方法分析与评价

图像均匀性及层厚是磁共振成像设备进行质量控制的主要性能参数.文章利用美国体膜实验室生产的Magphan SMR100体膜对磁共振成像设备的图像均匀性及层厚进行计量检测,分析了影响图像均匀性的各种因素以及图像不均匀对层厚测量带来的偏差,从而提高对磁共振成像设备周期检定的实践水平,确保磁共振成像设备图像清晰、可靠.     

基于不同体模的MRI图像均匀性和信噪比检测对比研究

探究了超导3.0T MRI设备和永磁0.4T MRI设备图像均匀性和信噪比检测的对比,分析了ACR体模和SMR 170体模检测结果的优劣.对于图像均匀性检测,ACR体模具有更高的灵敏度、真实度和更简便的检测流程.对于信噪比检测,需有效结合MRI设备性能,选择更合适的体模,建立相应的信噪比处置界限.     

医用磁共振成像(MRI)系统检测方法

医用磁共振成像(MRI)系统作为先进的大型医疗诊断设备,已广泛应用于大、中型医院。如何对磁共振影像进行评价,保证医用磁共振成像(MRI)系统各项性能正常和影像正确,一直没有统一的技术依据。本文根据医用磁共振成像(MRI)系统的技术特性,参考IEC标准和国家标准,验证和确定了检测参数和技术指标,研究制定出医用磁共振成像(MRI)系统检测方法,为医院质量控制,计量检定提供检测技术依据。     

浮法玻璃均匀性的光学检测方法

在浮法玻璃的生产中,均匀性的检测与控制对于玻璃的质量保证至关重要.本文给出了一种可有效用于浮法玻璃均匀性检测的光学方法.实验结果表明,该方法采用平行偏振光成像系统和CCD图像采集与处理技术,可以清楚地获得平板玻璃样品侧向均匀性分布的光学图像,并能对图像的灰度分布进行定量分析,从而可为玻璃的质量评价和工艺控制提供可靠的依据.     

内置式真空炉炉温均匀性检测系统

针对真空热处理设备无温度检测孔不能进行温度测试或真空炉因其结构的原因而造成的测试复杂等情况,设计制作在线检测系统并进行在线检测。     

射线数字成像检测系统不均匀性分析与校正

图像高低频畸变(即不均匀)会导致射线数字检测系统检测灵敏度的下降和误判,而造成畸变的原因是系统中射线源强度分布不均匀、闪烁体屏发光不均匀、镜头渐晕、科学级CCD暗电流和光响应不均匀。在此分析的基础上提出了一种校正方法,该方法利用实验得出校正矩阵,通过软件校正,先校正CCD暗电流和光响应不均匀性,再对其它三个因素合并校正。在便携式X射线源下,对三号透度计在15mm均匀钢板上的图像进行了校正实验,结果表明,灵敏度由校正前的1.67%提高到1.33%,图像不均匀性得到明显改善,空间分辨力大于3.5lp/mm。系统具有检测灵敏度高(≤1.5%)和适应射线能量范围大(50keV-15MeV)的优点。     

基于边缘检测的神经网络非均匀性校正及硬件实现

红外焦平面探测器的非均匀性校正技术仍然是当前红外热成像系统重点研究的关键技术之一。相对定标类算法,基于场景非均匀性校正根据场景进行非均匀参数更新,不需要使用挡板遮挡视场。本文介绍传统神经网络非均匀性校正算法及加快收敛速度的改进措施,引入边缘检测方法来克服传统神经网络算法的鬼影问题。文中阐述的方法已在以TMS320DM643为处理核心DSP硬件处理平台上实现,取得了较好的校正效果。     

电路板锡膏均匀性参数检测系统

建构了电路板锡膏的三维测量系统,实现了印刷锡膏均匀性参数的获取,从而达到对表面贴装质量进行监控和评价的目的．该系统基于线结构光测量原理,借助扫描技术实现三维轮廓测量．利用Tsai的径向排列约束法标定摄像机参数,由特制的棱角标定块实现光平面参数的标定．提出了电路板基层面自动确定方法,即根据图像特性实现锡膏和基层面的分离;并采用主元素分析法进行平面拟合,实现锡膏均匀性参数的计算和统计．采用该实验设备在半导体生产线上进行了大量测量,实验结果表明该系统操作简单、稳定可靠．     

Residual U-Network for Breast Tumor Segmentation from Magnetic Resonance Images

Breast cancer positions as the most well-known threat and the main source of malignant growth-related morbidity and mortality throughout the world. It is apical of all new cancer incidences analyzed among females. Two features substantially influence the classification accuracy of malignancy and benignity in automated cancer diagnostics. These are the precision of tumor segmentation and appropriateness of extracted attributes required for the diagnosis. In this research, the authors have proposed a ResU-Net (Residual U-Network) model for breast tumor segmentation. The proposed methodology renders augmented, and precise identification of tumor regions and produces accurate breast tumor segmentation in contrast-enhanced MR images. Furthermore, the proposed framework also encompasses the residual network technique, which subsequently enhances the performance and displays the improved training process. Over and above, the performance of ResU-Net has experimentally been analyzed with conventional U-Net, FCN8, FCN32. Algorithm performance is evaluated in the form of dice coefficient and MIoU (Mean Intersection of Union), accuracy, loss, sensitivity, specificity, F1score. Experimental results show that ResU-Net achieved validation accuracy & dice coefficient value of 73.22% & 85.32% respectively on the Rider Breast MRI dataset and outperformed as compared to the other algorithms used in experimentation.     

一种改进的MRI图像刚性平移运动伪影的校正

在磁共振成像过程中由于患者的运动会在图像中造成运动伪影,从而造成图像的退化,严重影响临床诊断．本文对MRI图像刚性平移运动伪影提出了一个改进的后处理方法：首先用谱平移理论消除频率编码方向平移运动;然后建立模糊模型表示图像的背景并对其进行抑制,用数学形态学的方法确定图像的支撑域;最后以能量熵为收敛准则,用相位恢复算法对频率编码方向残余的子像素移动造成的伪影和相位编码方向的伪影进行消除．实验表明,应用本研究提出的方法能够明显地消除图像空间运动造成的伪影．     

An Improved Jellyfish Algorithm for Multilevel Thresholding of Magnetic Resonance Brain Image Segmentations

Image segmentation is vital when analyzing medical images, especially magnetic resonance (MR) images of the brain. Recently, several image segmentation techniques based on multilevel thresholding have been proposed for medical image segmentation; however, the algorithms become trapped in local minima and have low convergence speeds, particularly as the number of threshold levels increases. Consequently, in this paper, we develop a new multilevel thresholding image segmentation technique based on the jellyfish search algorithm (JSA) (an optimizer). We modify the JSA to prevent descents into local minima, and we accelerate convergence toward optimal solutions. The improvement is achieved by applying two novel strategies: Ranking-based updating and an adaptive method. Ranking-based updating is used to replace undesirable solutions with other solutions generated by a novel updating scheme that improves the qualities of the removed solutions. We develop a new adaptive strategy to exploit the ability of the JSA to find a best-so-far solution; we allow a small amount of exploration to avoid descents into local minima. The two strategies are integrated with the JSA to produce an improved JSA (IJSA) that optimally thresholds brain MR images. To compare the performances of the IJSA and JSA, seven brain MR images were segmented at threshold levels of 3, 4, 5, 6, 7, 8, 10, 15, 20, 25, and 30. IJSA was compared with several other recent image segmentation algorithms, including the improved and standard marine predator algorithms, the modified salp and standard salp swarm algorithms, the equilibrium optimizer, and the standard JSA in terms of fitness, the Structured Similarity Index Metric (SSIM), the peak signal-to-noise ratio (PSNR), the standard deviation (SD), and the Features Similarity Index Metric (FSIM). The experimental outcomes and the Wilcoxon rank-sum test demonstrate the superiority of the proposed algorithm in terms of the FSIM, the PSNR, the objective values, and the SD; in terms of the SSIM, IJSA was competitive with the others.     

SQUID-Detected Magnetic Resonance Imaging in Microtesla Magnetic Fields

We describe studies of nuclear magnetic resonance (NMR) spectroscopy and magnetic resonance imaging (MRI) of liquid samples at room temperature in microtesla magnetic fields. The nuclear spins are prepolarized in a strong transient field. The magnetic signals generated by the precessing spins, which range in frequency from tens of Hz to several kHz, are detected by a low-transition temperature dc SQUID (Superconducting QUantum Interference Device) coupled to an untuned, superconducting flux transformer configured as an axial gradiometer. The combination of prepolarization and frequency-independent detector sensitivity results in a high signal-to-noise ratio and high spectral resolution (～1 Hz) even in grossly inhomogeneous magnetic fields. In the NMR experiments, the high spectral resolution enables us to detect the 10-Hz splitting of the spectrum of protons due to their scalar coupling to a ³¹P nucleus. Furthermore, the broadband detection scheme combined with a non-resonant field-reversal spin echo allows the simultaneous observation of signals from protons and ³¹P nuclei, even though their NMR resonance frequencies differ by a factor of 2.5. We extend our methodology to MRI in microtesla fields, where the high spectral resolution translates into high spatial resolution. We demonstrate two-dimensional images of a mineral oil phantom and slices of peppers, with a spatial resolution of about 1 mm. We also image an intact pepper using slice selection, again with 1-mm resolution. In further experiments we demonstrate T₁-contrast imaging of a water phantom, some parts of which were doped with a paramagnetic salt to reduce the longitudinal relaxation time T₁. Possible applications of this MRI technique include screening for tumors and integration with existing multichannel SQUID systems for brain imaging.     

Rapid, Embeddable Design Method for Spiral Magnetic Resonance Image Reconstruction Resampling Kernels

After formulating the design problem for Resampling Kernels used in Magnetic Resonance Spiral Image Reconstruction, we show that an iterative Gauss-Seidel-type interior-point optimization method is suitable (fast and light-weight) for embedded uses. In contrast to previous practice, we directly optimize a computationally efficient, piecewise-linear kernel rather than an analytic function (Kaiser-Bessel). We also optimize our kernels for worst-case (infinity-norm) signal aliasing, rather than the usual proxy energy function (2-norm) minimization. In numerical simulations of undesirable near-frequency systematic noise the new kernel significantly outperforms a conventional Kaiser-Bessel-based solution.     

Quantification of Pelvic Mobility on Dynamic Magnetic Resonance Images: Using Mechanical Insight to Help Diagnose Pelvic Pathologies

Pelvic mobility is essential for good pelvic organ function. Any modification may be a sign of pathology. The objective of this study was to define a methodology to quantify pelvic mobility. An analysis protocol based on an image registration technique performed on dynamic magnetic resonance imaging sequences is presented. A methodology is proposed for measuring and analysing the whole displacement field based on the contour of the four pelvic organs: the vagina, bladder, rectum and uterus. A targeted analysis of pelvic mobility can be applied in the normal, hypermobility and hypomobility context. The quantification of pelvic mobility in normal conditions allows localising fascia or ligaments involved in the static of pelvic organs. In pathological situations such as prolapse, it helps localise a suspension structure weakness. In a context of hypomobility such as deep pelvic endometriosis, it should help localise pathologic areas to provide more relevant diagnosis and treatment. When combined with conventional radiology, this analysis protocol can be applied to the diagnosis and assessment of complex pelvic pathologies to help define the most suitable surgery. Moreover, these experimental results obtained in normal and pathological cases will help build and validate a better mechanical finite element model of the pelvic system.     

多元红外探测器均匀性自动化测试

针对光导型多元红外探测器特性,研制了红外探测器均匀性自动化测试系统.本文介绍了测试系统的组成及相应的软件,阐述了工作原理、控制策略及数据处理技术.测试结果表明系统设计合理、工作稳定,具有精确控制和抗干扰能力.     

两类鞍形线圈产生磁场均匀性效能的研究

以毕奥-萨伐尔定律在笛卡尔直角坐标下对两种鞍形匀场线圈进行数学建模,通过对两种轴对称线圈单组的数值分析得出线圈系统在径向磁场分布的一般特征,在理论计算获得线圈最佳结构下利用Matlab优化结构参数。对比了这两类鞍形线圈在轴上和空间立方体的磁场均匀区大小及与中心磁场的相对偏差。并给出了这两种线圈磁场相对偏差ε≤1%的有效匀场空间区域,为主动屏蔽系统的线圈类型选择提供了参考依据。     

大视场线阵CCD图像灰度均匀化

针对大视场线阵 CCD 图像不均匀现象,提出了一种基于图像像素灰度补偿的均匀化方法。首先分析并计算线形目标上不同坐标位置的微小面元在线阵CCD上产生的辐射照度,并由此推导线阵CCD面元上不同像素灰度值与中心像素灰度值之间的关系,进而建立大视场线阵CCD像面上像素的灰度补偿模型,实现大视场线阵CCD图像快速均匀化的目的。对大量线阵 CCD 采集的高速路面图像进行了处理,结果表明我们提出的方法具有较强的可行性、鲁棒性和实用性。